Ontological Detection of Phishing Emails

Detection of phishing emails is a topic that received a lot of attention both from academia and industry due to the devastating effects of phishing enabled data breaches have on private individual and companies. While the accuracy of phishing detection reported in the papers is impressive, the damage from the attacks continues to grow every year. One of the reasons is the diversity of attacks, especially within spear phishing and whaling. Another reason is that the natural language part of the detectors is usually devoid of semantics. In this paper we present an approach that adds semantics to highly accurate bag of words and part of speech approaches. We show that while the current approach is less accurate as a starting point, it retains its accuracy as a corpus deviates from training, while the accuracy of the original approach decreases with the amount of deviations.